Human gait is an attractive modality for recognizing people at a distance. In this paper we adopt an appearance-based approach to the problem of gait recognition. The width of the outer contour of the binarized silhouette of a walking person is chosen as the basic image feature. Different gait features are extracted from the width vector such as the dowsampled, smoothed width vectors, the velocity profile etc. and sequences of such temporally ordered feature vectors are used for representing a person's gait. We use the dynamic time-warping (DTW) approach for matching so that non-linear time normalization may be used to deal with the naturally-occuring changes in walking speed. The performance of the proposed method is tested using different gait databases. © Springer-Verlag 2003.
CITATION STYLE
Kale, A., Cuntoor, N., Yegnanarayana, B., Rajagopalan, A. N., & Chellappa, R. (2003). Gait analysis for human identification. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2688, 706–714. https://doi.org/10.1007/3-540-44887-x_82
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